Table 4.

Evaluation of trained models.

Model	Train			Test
	RMSE	MAE	MAPE	RMSE	MAE	MAPE
LightGBM	0.1914 ± 0.0014	0.1461 ± 0.0013	0.9237 ± 0.0285	0.1900 ± 0.0124	0.1471 ± 0.0044	0.8027 ± 0.064
XGBoost	0.1752 ± 0.0011	0.1322 ± 0.0012	1.3979 ± 0.052	0.1977 ± 0.0065	0.1485 ± 0.0042	1.5565 ± 0.1633
CatBoost	0.1787 ± 0.0013	0.1346 ± 0.0011	1.3992 ± 0.0525	0.1991 ± 0.0095	0.1473 ± 0.0043	1.5212 ± 0.1643
AdaBoost	0.1945 ± 0.0017	0.1461 ± 0.0013	1.5437 ± 0.0476	0.1957 ± 0.0073	0.1504 ± 0.0030	1.5510 ± 0.1684
SVR	0.1828 ± 0.0091	0.1386 ± 0.0045	1.2952 ± 0.0590	0.1954 ± 0.0073	0.1475 ± 0.0048	1.6571 ± 0.1212
MLP	0.1961 ± 0.0017	0.1433 ± 0.0016	0.7828 ± 0.0245	0.1975 ± 0.0075	0.1499 ± 0.0075	0.9246 ± 0.1048
MLR	0.1806 ± 0.0076	0.1409 ± 0.0057	1.4872 ± 0.1653	0.1955 ± 0.0075	0.1479 ± 0.0058	1.6607 ± 0.3333

The mean ± standard deviation was reported.